<b>Identification of Rainfall Homogenous Regions taking into account El Niño and La Niña and Rainfall Decrease in the state of Pará, Brazilian Amazon

Abstract

The statistical analysis of rainfall data is a tool to identify homogenous clusters which reveal the behavior pattern of the rainfall regime in a given region. Current study identifies homogenous clusters in the state of Pará in the Amazon region, Brazil, with rainfall data for 413 monitored sites. A 31-year historical series was used (1960-1990) and the years with the occurrence of El Niño and La Niña were selected. Ward’s Hierarchical Agglomerative Clustering Method was employed with Euclidean distance used as a similarity measurement. Results generated homogenous rainfall clusters for the state of Pará. A similarity in rainfall rates for the homogenous clusters was constructed which made possible the need to identify and analyze the importance of taking into consideration El Niño and La Niña to determine homogenous rainfall regions. One may also identify regions with low rainfall rates, which may represent climate changes caused by change in land use, as in the southeastern region of Pará, where agriculture and ranching have been replacing the Amazon forest for the last forty years.

Keywords

• climate change
• cluster analysis
• Ward method